Jobs at Micron Technology

Leads cross-functional strategic programs focused on cost savings, supplier engagement, capacity readiness, operating cadence, governance, and organizational effectiveness. Coordinates executive forums, tracks risks and decisions, prepares leadership updates, and manages people-focused capability-building initiatives. Partners across technical, operational, business, and supplier stakeholders to translate priorities into measurable execution plans and improve organizational efficiency through digital, analytical, automation, and AI-assisted workflows.

Lead NAND-CMOS device development: define and execute silicon experiments, set transistor targets and models, partner with TCAD and Design, create electrical test structures, ensure reliability and yield with Manufacturing, mentor junior engineers, and leverage AI/Agent-AI tools to automate workflows and improve device performance and cost.

Develop an AI-enabled application, analytical model, or automated workflow addressing a semiconductor process or equipment engineering challenge. Analyze manufacturing and engineering data using statistics, machine learning, Generative AI, large language models, visualization, or automation. Test, validate, document, and present the solution, demonstrating potential improvements in yield, quality, cost, productivity, or cycle time.

Designs and delivers agentic AI systems that transform complex business processes into autonomous, scalable workflows. Responsibilities include process decomposition, AI architecture, agent and tool orchestration, prompt and context strategy, prototyping, security controls, human-in-the-loop design, testing, cross-functional delivery, value measurement, and mentoring. The role requires collaboration with business, architecture, security, platform engineering, and project management teams through production release.

Develop and operate cloud-based data platforms and scalable ETL pipelines for NAND reliability engineering. Analyze large semiconductor and manufacturing datasets using Python, SQL, BigQuery, and PySpark. Develop and deploy AI/ML solutions for failure analysis, anomaly detection, reliability assessment, and engineering decision-making. Collaborate with IT, AI, quality, manufacturing, and engineering teams; communicate technical findings; support customer reliability inquiries; and promote AI-enabled productivity improvements.

Develop and deploy optimization, simulation, and ML models to improve semiconductor factory capacity, throughput, and cycle time. Partner with cross-functional manufacturing and engineering teams to analyze constraints, run scenario analyses, and deliver data-driven recommendations integrated into production pipelines and decision-support tools.

Five-month intern project focused on NAND probe product engineering, test mode integration, Design for Test, silicon validation, and product characterization. The intern will analyze engineering data for yield and failure patterns, develop visualization and automation tools, and explore AI, machine learning, generative AI, and LLM-based solutions for engineering workflows. Deliverables include technical assessments, dashboards, prototypes, reports, and recommendations.

Manage the lifecycle of software applications supporting automated semiconductor manufacturing. Analyze business and technical requirements, develop secure solutions, oversee testing and releases, apply patches, monitor systems, prevent downtime, and provide technical guidance. The role also involves end-user training, collaboration with global IT teams, software project management, Agile development, and adoption of AI-powered tools to improve delivery and operational efficiency.

Owns end-to-end reliability architecture and qualification strategies for NAND products. Responsibilities include designing stress and sampling plans, developing reliability test flows and system features, optimizing test time, investigating failures, analyzing reliability datasets, and supporting product release. The role requires cross-functional technical leadership across design, firmware, manufacturing, quality, and systems teams, plus automation and AI-enabled workflow development.

Leads semiconductor wafer fabrication shift operations for NAND technology development, resolving process and equipment issues, managing critical lots and excursions, supporting yield and quality improvements, and coordinating with engineering, manufacturing, and suppliers. Provides technical guidance, drives data-based root-cause resolution, manages capacity and improvement plans, and develops shift team performance through coaching, training, prioritization, and project leadership.

Develop an end-to-end analytics and machine learning solution for semiconductor manufacturing data. Analyze electrical, physical, inline, and probe measurements; perform data querying, preprocessing, feature engineering, modeling, optimization, and visualization; and create predictive models and drift-detection methods to improve production-line monitoring and engineering decisions. The intern will document and present findings while collaborating with manufacturing engineering teams.

Develop and optimize semiconductor assembly and packaging processes, characterize process windows, improve yield and reliability, and lead root-cause and failure-analysis investigations. Support NPI, product qualification, technology transfers, process readiness, and high-volume manufacturing. Use statistical methods, manufacturing datasets, visualization, machine learning, and AI-enabled monitoring to identify trends and optimize processes. Provide technical leadership, mentor engineers, and coordinate cross-functional teams across process development, manufacturing, yield, reliability, integration, and equipment engineering.

Lead cross-functional semiconductor process integration efforts to improve fab yield and reliability. Design, run, and analyze experiments, collaborate with global fab teams, communicate module issues, and standardize best-known methods to optimize processes and forecast yield and output.

Develops and optimizes photolithography processes for advanced 3D NAND manufacturing. Responsibilities include applying AI to process development, improving yield and quality, evaluating hardware and novel processes, troubleshooting cross-functional issues, implementing process monitoring and control, supporting future technology nodes, and generating patents or technical publications. The role also involves collaboration with global R&D teams, vendors, suppliers, and manufacturing partners, with potential travel for collaborative research.

Design, develop, and test embedded firmware subsystems for SSD products to meet performance, endurance, capacity, and reliability goals. Create unit and functional tests, debug firmware, communicate progress to stakeholders, mentor teammates, collaborate cross-functionally, and integrate AI-assisted tools to improve development efficiency and quality.

The role involves improving manufacturing operations through analytics, project management, collaboration, and effective communication of solutions using programming and machine learning skills.

Supports program management for a semiconductor fabrication conversion and new product introduction. Responsibilities include developing project plans, tracking milestones, assessing manufacturing readiness, identifying risks, analyzing engineering and manufacturing data, creating dashboards, and preparing management communications. The intern collaborates with engineering and manufacturing teams while gaining experience in semiconductor processes, project planning, risk management, stakeholder coordination, and process improvement.

Provides first-line troubleshooting and support for manufacturing software applications and system solutions. Assists with application deployment, maintenance, performance monitoring, user-interface improvements, database health, backup and recovery, documentation, and issue escalation. Collaborates with business users, IT, and engineering teams to improve operational efficiency using automation and AI-enabled tools. Works rotating 12-hour shifts, including nights, and supports training and knowledge sharing.

Lead definition, development, and delivery of Industry 4.0 smart manufacturing products. Own product roadmap, gather and prioritize requirements, coordinate engineering, data science, and operations, deploy data-driven solutions, ensure data quality, build UI visualizations, and scale standardized tools and processes across global sites.

Designs and delivers agentic AI systems that transform complex manual business processes into secure, scalable autonomous workflows. Responsibilities include process decomposition, AI architecture, agent and prompt design, integrations, prototyping, testing, human-in-the-loop controls, least-privilege security, cross-functional delivery, value measurement, and mentoring. The role requires strong business-process redesign experience alongside hands-on AI/ML and LLM system development.